Towards Robust Autonomous Underwater Docking for Long-Term Under-Ice Exploration

Autonomous underwater docking is a necessary requirement for achieving long-term term residency for Autonomous Underwater Vehicles (AUVs). In this work, we propose a docking method that is capable of achieving robust docking by proposing a state machine and extending our localization framework with visual features from Apriltag marker measurements and USBL 2D position measurements. In total we executed 201 docking sequences of which 194 were succesful, thus yielding a total success rate of 96.5%. To further test the robustness of the proposed method, multiple experiments were conducted where feedback from visual markers was actively denied during the approach of the vehicle to its designated docking station. Our results show that the proposed method was able to complete 73 successful docking maneuvers out of 76 attempts (96%) without any visual aiding.